DenseNet-121: Optimized for Qualcomm Devices

Densenet is a machine learning model that can classify images from the Imagenet dataset. It can also be used as a backbone in building more complex models for specific use cases.

This is based on the implementation of DenseNet-121 found here. This repository contains pre-exported model files optimized for Qualcomm® devices. You can use the Qualcomm® AI Hub Models library to export with custom configurations. More details on model performance across various devices, can be found here.

Qualcomm AI Hub Models uses Qualcomm AI Hub Workbench to compile, profile, and evaluate this model. Sign up to run these models on a hosted Qualcomm® device.

Getting Started

There are two ways to deploy this model on your device:

Option 1: Download Pre-Exported Models

Below are pre-exported model assets ready for deployment.

Runtime	Precision	Chipset	SDK Versions	Download
ONNX	float	Universal	QAIRT 2.42, ONNX Runtime 1.24.3	Download
QNN_DLC	float	Universal	QAIRT 2.45	Download
QNN_DLC	w8a8_mixed_int16	Universal	QAIRT 2.45	Download
TFLITE	float	Universal	QAIRT 2.45	Download

For more device-specific assets and performance metrics, visit DenseNet-121 on Qualcomm® AI Hub.

Option 2: Export with Custom Configurations

Use the Qualcomm® AI Hub Models Python library to compile and export the model with your own:

• Custom weights (e.g., fine-tuned checkpoints)
• Custom input shapes
• Target device and runtime configurations

This option is ideal if you need to customize the model beyond the default configuration provided here.

See our repository for DenseNet-121 on GitHub for usage instructions.

Model Details

Model Type: Model_use_case.image_classification

Model Stats:

• Model checkpoint: Imagenet
• Input resolution: 224x224
• Number of parameters: 7.99M
• Model size (float): 30.5 MB
• Model size (w8a16): 8.72 MB
• Model size (w8a8): 8.30 MB

Performance Summary

Model	Runtime	Precision	Chipset	Inference Time (ms)	Peak Memory Range (MB)	Primary Compute Unit
DenseNet-121	ONNX	float	Snapdragon® 8 Elite Gen 5 Mobile	0.675 ms	0 - 46 MB	NPU
DenseNet-121	ONNX	float	Snapdragon® X2 Elite	0.741 ms	16 - 16 MB	NPU
DenseNet-121	ONNX	float	Snapdragon® X Elite	1.744 ms	15 - 15 MB	NPU
DenseNet-121	ONNX	float	Snapdragon® 8 Gen 3 Mobile	1.077 ms	0 - 88 MB	NPU
DenseNet-121	ONNX	float	Qualcomm® QCS8550 (Proxy)	1.519 ms	0 - 17 MB	NPU
DenseNet-121	ONNX	float	Qualcomm® QCS9075	2.61 ms	1 - 3 MB	NPU
DenseNet-121	ONNX	float	Snapdragon® 8 Elite For Galaxy Mobile	0.787 ms	0 - 46 MB	NPU
DenseNet-121	QNN_DLC	float	Snapdragon® 8 Elite Gen 5 Mobile	0.719 ms	1 - 42 MB	NPU
DenseNet-121	QNN_DLC	float	Snapdragon® X2 Elite	0.95 ms	1 - 1 MB	NPU
DenseNet-121	QNN_DLC	float	Snapdragon® X Elite	2.036 ms	1 - 1 MB	NPU
DenseNet-121	QNN_DLC	float	Snapdragon® 8 Gen 3 Mobile	1.211 ms	0 - 76 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® QCS8275 (Proxy)	7.878 ms	1 - 38 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® QCS8550 (Proxy)	1.792 ms	1 - 3 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® SA8775P	2.695 ms	1 - 40 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® QCS9075	2.757 ms	1 - 3 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® QCS8450 (Proxy)	3.288 ms	0 - 75 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® SA7255P	7.878 ms	1 - 38 MB	NPU
DenseNet-121	QNN_DLC	float	Qualcomm® SA8295P	3.075 ms	1 - 36 MB	NPU
DenseNet-121	QNN_DLC	float	Snapdragon® 8 Elite For Galaxy Mobile	0.88 ms	0 - 38 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Snapdragon® 8 Elite Gen 5 Mobile	1.164 ms	0 - 69 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Snapdragon® X2 Elite	1.466 ms	0 - 0 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Snapdragon® X Elite	3.206 ms	0 - 0 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Snapdragon® 8 Gen 3 Mobile	2.079 ms	0 - 83 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Qualcomm® QCS8275 (Proxy)	5.937 ms	0 - 62 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Qualcomm® QCS8550 (Proxy)	2.978 ms	0 - 2 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Qualcomm® SA8775P	3.281 ms	0 - 65 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Qualcomm® QCS9075	3.257 ms	0 - 2 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Qualcomm® SA7255P	5.937 ms	0 - 62 MB	NPU
DenseNet-121	QNN_DLC	w8a8_mixed_int16	Snapdragon® 8 Elite For Galaxy Mobile	1.563 ms	0 - 57 MB	NPU
DenseNet-121	TFLITE	float	Snapdragon® 8 Elite Gen 5 Mobile	0.721 ms	0 - 56 MB	NPU
DenseNet-121	TFLITE	float	Snapdragon® 8 Gen 3 Mobile	1.208 ms	0 - 89 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® QCS8275 (Proxy)	7.939 ms	0 - 52 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® QCS8550 (Proxy)	1.828 ms	0 - 3 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® SA8775P	2.713 ms	0 - 56 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® QCS9075	2.81 ms	0 - 18 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® QCS8450 (Proxy)	3.304 ms	0 - 87 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® SA7255P	7.939 ms	0 - 52 MB	NPU
DenseNet-121	TFLITE	float	Qualcomm® SA8295P	3.062 ms	0 - 49 MB	NPU
DenseNet-121	TFLITE	float	Snapdragon® 8 Elite For Galaxy Mobile	0.881 ms	0 - 50 MB	NPU

License

• The license for the original implementation of DenseNet-121 can be found here.

References

• Densely Connected Convolutional Networks
• Source Model Implementation

Community

• Join our AI Hub Slack community to collaborate, post questions and learn more about on-device AI.
• For questions or feedback please reach out to us.